A lightweight automatic sleep staging method for children using single-channel EEG based on edge artificial intelligence

Article Biochemical Research Methods

Hybrid manifold-deep convolutional neural network for sleep staging

Chuanhao Zhang et al.

Summary: This study introduces a novel hybrid manifold-deep convolutional neural network with hyperbolic attention module and semi-supervised training scheme, achieving promising results by extracting latent feature representation.

METHODS (2022)

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Article Engineering, Biomedical

Competition convolutional neural network for sleep stage classification

Junming Zhang et al.

Summary: A new unsupervised competitive convolutional neural network (C-CNN) model is proposed in this study, achieving better performance than baseline models in sleep stage classification. By applying convolutional operators, competitive operators, and pooling operators, the C-CNN model can effectively extract features from EEG signals and learn the distribution of input samples.

BIOMEDICAL SIGNAL PROCESSING AND CONTROL (2021)

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Article Computer Science, Information Systems

WAEAS: An Optimization Scheme of EAS Scheduler for Wearable Applications

Zhan Zhang et al.

Summary: The rapid development of wearable computing technologies has increased the integration of wearable devices into people's daily lives. Researchers are focusing on improving the battery life and performance of wearable devices by optimizing the Energy-Aware Scheduler, providing better energy management for wearable applications.

TSINGHUA SCIENCE AND TECHNOLOGY (2021)

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Article Computer Science, Information Systems

Inertial Motion Tracking on Mobile and Wearable Devices: Recent Advancements and Challenges

Zhipeng Song et al.

Summary: Motion tracking using Inertial Measurement Units (IMUs) on mobile and wearable devices has gained significant interest recently. Despite the advancements over the past two decades, there are still key challenges in IMU-based motion tracking that require further exploration and solutions. Researchers have been continuously improving IMU technology, from calibration techniques to motion models, in order to address these challenges.

TSINGHUA SCIENCE AND TECHNOLOGY (2021)

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Article Engineering, Industrial

Digital Twin-driven online anomaly detection for an automation system based on edge intelligence

Huiyue Huang et al.

Summary: This paper introduces a novel Digital Twin-driven anomaly detection framework for real-time health monitoring and anomaly prediction of industrial systems using edge intelligence technology. The adoption of Digital Twin technology enables efficient data processing and high-performance anomaly detection in industrial systems.

JOURNAL OF MANUFACTURING SYSTEMS (2021)

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Proceedings Paper Computer Science, Artificial Intelligence

CareEdge: A Lightweight Edge Intelligence Framework for ECG-Based Heartbeat Detection

Penghua Zhen et al.

Summary: The large-scale application of Internet of Things technology has brought more attention to the edge of the network, where a large amount of data generated requires AI processing, leading to the development of Edge Intelligence. The novel and lightweight CareEdge framework promotes IoT-Edge-Cloud integration, provides a good interface for IoT smart applications, and effectively utilizes related resources by offering data analysis programs for multiple users. CareEdge has demonstrated lower latency than similar frameworks in the experiment, showcasing its effectiveness.

2020 INTERNATIONAL CONFERENCE ON IDENTIFICATION, INFORMATION AND KNOWLEDGE IN THE INTERNET OF THINGS (IIKI2020) (2021)

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Article Computer Science, Artificial Intelligence

Effect of E-Learning on Public Health and Environment During COVID-19 Lockdown

Avani Agarwal et al.

Summary: E-learning is considered the most promising venture worldwide. This paper examines the efficiency and acceptability of e-learning tools among Indian students during the COVID-19 lockdown, and evaluates the impact of e-learning on the environment and public health during this period. While e-learning has the potential to reduce carbon emissions, it may also have negative effects on mental and physical health due to increased screen time.

BIG DATA MINING AND ANALYTICS (2021)

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Article Computer Science, Theory & Methods